Type 1 diabetes mellitus induces structural changes and molecular remodelling in the rat kidney

There is much evidence that diabetes mellitus (DM) –induced hyperglycemia (HG) is responsible for kidney failure or nephropathy leading to cardiovascular complications. Cellular and molecular mechanism(s) whereby DM can damage the kidney is still not fully understood. This study investigated the effect of streptozotocin (STZ)-induced diabetes (T1DM) on the structure and associated molecular alterations of the isolated rat left kidney following 2 and 4 months of the disorder compared to the respective age-matched controls. The results revealed hypertrophy and general disorganized architecture of the kidney characterized by expansion in glomerular borders, tubular atrophy and increased vacuolization of renal tubular epithelial cells in the diabetic groups compared to controls. Electron microscopic analysis revealed ultrastructural alterations in the left kidney highlighted by an increase in glomerular basement membrane width. In addition, increased caspase-3 immuno-reactivity was observed in the kidney of T1DM animals compared to age-matched controls. These structural changes were associated with elevated extracellular matrix (ECM) deposition and consequently, altered gene expression profile of ECM key components, together with elevated levels of key mediators (MMP9, integrin 5α, TIMP4, CTGF, vimentin) and reduced expressions of Cx43 and MMP2 of the ECM. Marked hypertrophy of the kidney was highlighted by increased atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) gene expression. These changes also correlated with increased TGFβ1 activity, gene expression in the left kidney and elevated active TGFβ1 in plasma of T1DM rats compared to control. The results clearly demonstrated that TIDM could elicit severe structural changes and alteration in biochemical markers (remodeling) in the kidney leading to diabetic nephropathy (DN)

Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

© 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (RCM), by incorporating the physically based SNow ICe And Radiative (SNICAR) scheme. SNICAR simulates snow albedo evolution due to snow aging and presence of aerosols in snow. The land surface model is further modified to account for deposition, movement, and removal by meltwater of such impurities in the snowpack. This paper presents model development technique, validation with in situ observations, and preliminary results from RCM simulations investigating the impact of such impurities in snow on surface energy and water budgets. By including snow-aerosol interactions, the new land surface model is able to realistically simulate observed snow albedo, snow grain size, dust in snow, and surface water and energy balances in offline simulations for a location in western U.S. Preliminary results with the fully coupled RCM show that over western U.S., realistic aerosol deposition in snow induces a springtime average radiative forcing of 16W/m2 due to a 6% albedo reduction, a regional surface warming of 0.84°C, and a snowpack reduction of 11mm

Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

© 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (RCM), by incorporating the physically based SNow ICe And Radiative (SNICAR) scheme. SNICAR simulates snow albedo evolution due to snow aging and presence of aerosols in snow. The land surface model is further modified to account for deposition, movement, and removal by meltwater of such impurities in the snowpack. This paper presents model development technique, validation with in situ observations, and preliminary results from RCM simulations investigating the impact of such impurities in snow on surface energy and water budgets. By including snow-aerosol interactions, the new land surface model is able to realistically simulate observed snow albedo, snow grain size, dust in snow, and surface water and energy balances in offline simulations for a location in western U.S. Preliminary results with the fully coupled RCM show that over western U.S., realistic aerosol deposition in snow induces a springtime average radiative forcing of 16W/m2 due to a 6% albedo reduction, a regional surface warming of 0.84°C, and a snowpack reduction of 11mm

Radiative forcing by light-absorbing particles in snow

As one of the brightest natural surfaces on Earth, the darkening of snow by light-absorbing particles (LAPs) — dust, black carbon or microbial growth — can trigger albedo feedbacks and accelerate snowmelt. Indeed, an increase in black carbon deposition following the industrial revolution has led to the recognition that LAP radiative forcing has contributed to a reduction in the global cryosphere, with corresponding climatic impacts. This Review synthesizes our current understanding of the distribution of radiative forcing by LAPs in snow, and discusses the challenges that need to be overcome to constrain global impacts, including the limited scope of local-scale observations, limitations of remote sensing technology and the representation of LAP-related processes in Earth system models